A new research project promoted by ESAC, with the support of Novartis Farma S.p.A., is officially underway. The project focuses on studying the use of synthetic data in breast cancer research and has been launched with the aim of evaluating the usefulness of synthetic data in the field of cancer research and care.
“Through this project, we aim to understand whether synthetic data can support robust analyses, with levels of accuracy and reliability comparable to those of the real clinical data currently available to us, including in terms of the resulting outputs,” says Arsela Prelaj, President of ESAC. “At the same time, it will allow us to address the need for high-quality, homogeneous source data, an essential requirement to ensure reliable results in any AI application especially in medicine and oncology, given the variety and complexity of the information required for diagnosis and therapeutic decision-making.”
Synthetic data are defined as data generated by AI algorithms based on real datasets. They faithfully reproduce the characteristics of real data without containing any information related to actual patients. This makes it possible to overcome many of the challenges that currently limit access to and sharing of health data, which are subject to necessary but stringent ethical, regulatory, and organizational requirements.
At the same time, synthetic data ensure a high level of privacy protection, making them easier to use for collaborative research and analytical activities. Working with data that are not linked to real patients simplifies authorization processes and creates the conditions for smoother and safer information sharing, both for the institutions involved in the analyses and for patients themselves.
“Looking to the future, the use of synthetic data opens up opportunities to experiment with new research approaches, such as the simulation of treatment pathways, the evaluation of different treatment scenarios, or the preliminary design of clinical studies,” concludes Arsela Prelaj “These innovations can make oncology research more efficient; the challenge now is to translate them into concrete applications that can be used in real-world settings. I believe that collaborative projects like this make it possible to meet this challenge by balancing innovation and scientific rigor, in full respect of ethical principles.”
The six-month project represents a concrete step toward assessing the role of synthetic data as a tool supporting oncology research, with the long-term goal of fostering the development of more innovative, secure, and sustainable research models.